基于Visual C++的单板表面缺陷图像检测软件开发与应用  

An Image Detection Program for Veneer Surface Defects Based on Visual C++

作　　者：程玉柱[1] 李赵春[1] CHENG Yu-zhu;LI Zhao-chun(College of Mechanical and Electronic Engineering,Nanjing Forestry University,Nanjing 210037,Jiangsu,China)

机构地区：[1]南京林业大学机械电子工程学院,江苏南京210037

出　　处：《木材工业》2018年第6期41-44,共4页China Wood Industry

基　　金：南京林业大学大学生创新项目"基于分数阶流形学习理论的图像分割算法研究"(2015sjcx050)

摘　　要：针对单板中的死节与裂缝缺陷,利用VisualC++2017(VC++)与OpenCV编写缺陷图像检测程序。先将RGB图像进行分数阶主成份(principal component analysis,PCA)转换,再对得到的三通道灰度图像进行Chan-Vese (CV)分割;最后对二值图像面积滤波,根据长宽比检测出死节与裂缝。结果显示:此程序可去除大部分噪声,很好地实现单板表面死节和裂缝缺陷的提取和检测。A wood defect image detection program was developed using Visual C++2017(VC++)and Open CV to detect dead knots and cracks in veneers.First,RGB images were transformed into gray images with fractional-order principal component analysis(PCA).Then,three channel gray images were segmented with the Chan-Vese(CV)model.Finally,binary images were filtered according to a length-width ratio to detect the dead knots and cracks.The experimental results showed that the algorithm could be used to remove most noise to extract dead knots and cracks in veneers.

关 键 词：单板 表面缺陷 死节 裂缝 VISUALC++ 分数阶 主成份分析 CV模型 

分 类 号：S781.5[农业科学—木材科学与技术] TS653.2[农业科学—林学]